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J Epidemiol. 2014;24(2):161-7. Epub 2013 Dec 7.

Is a cutoff of 10% appropriate for the change-in-estimate criterion of confounder identification?

Author information

1
School of Public Health, University of Hong Kong.

Abstract

BACKGROUND:

When using the change-in-estimate criterion, a cutoff of 10% is commonly used to identify confounders. However, the appropriateness of this cutoff has never been evaluated. This study investigated cutoffs required under different conditions.

METHODS:

Four simulations were performed to select cutoffs that achieved a significance level of 5% and a power of 80%, using linear regression and logistic regression. A total of 10 000 simulations were run to obtain the percentage differences of the 4 fitted regression coefficients (with and without adjustment).

RESULTS:

In linear regression, larger effect size, larger sample size, and lower standard deviation of the error term led to a lower cutoff point at a 5% significance level. In contrast, larger effect size and a lower exposure-confounder correlation led to a lower cutoff point at 80% power. In logistic regression, a lower odds ratio and larger sample size led to a lower cutoff point at a 5% significance level, while a lower odds ratio, larger sample size, and lower exposure-confounder correlation yielded a lower cutoff point at 80% power.

CONCLUSIONS:

Cutoff points for the change-in-estimate criterion varied according to the effect size of the exposure-outcome relationship, sample size, standard deviation of the regression error, and exposure-confounder correlation.

PMID:
24317343
PMCID:
PMC3983286
DOI:
10.2188/jea.je20130062
[Indexed for MEDLINE]
Free PMC Article

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